The other answers here have dealt with the idea of the definition of the derivative excellently, however, there are a couple of things I would like to add that may enhance your understanding of what a derivative actually means, and why it is even useful or cool.
In the first place, we can unpack the definition by observing what we are actually doing when we write the definition down. To do this, let's take you back to talking about the "gradient" of a straight line segment that exists between two points.
Suppose we have some nice function $f(x)$ (more on what that means later) and we have two points, whose $x$ values are given by $x$ and another point some distance $h$ away, $x+h$ (where $h \neq 0$, otherwise we would be at exactly the same point).
Then our two points are given by $(x, f(x))$ and $(x+h, f(x+h))$. To compute the gradient between these two points, we simply divide the difference between the $y$ values by the difference in the $x$ values, thereby computing the so-called "rise over run":
\begin{align}
\text{gradient} &= \frac{f(x+h) - f(x)}{(x+h) - x}
\\
&= \frac{f(x+h) - f(x)}{h}
\end{align}
This should look familiar to you, as it looks *almost like the definition of the derivative. The derivative is defined by looking at this expression for the gradient, and seeing what happens as you let the value $h$ get closer and closer to $0$:
\begin{align}
f'(x) = \lim_{h \to 0} \frac{f(x+h) - f(x)}{h}
\end{align}
Remember, that this formula is taking two points, and computing the gradient of the straight line segment between those two points. If $h$ is some huge number and we have a wacky function, then the straight line won't line up very well at all with the graph of the function! But, if our function is "nice" enough, then if we set $h$ to be very very small, it starts to look like the straight line segment and the function are the same thing (in that small neighborhood around $x$). If you open up a graphing application, and type in $f(x) = x^2$, for example, and around $x=2$ if you keep zooming in closer and closer and closer to the function, it will start to look less "curvy" and more and more like a straight line! In fact, the straight line passing through the point $(2,4)$ with gradient $4$ (i.e. $g(x) = 4x - 4)$ will look exactly like the function $f(x) = x^2$ if you zoom in close enough.
$x^2$ and $4x - 4$ are clearly different, even if they touch at $(2,4)$">

And that's the point, in the *limit as $h$ moves to 0, we can then approximate how the function $f(x)$ is changing around some point $x$ by a straight line with a gradient given by $f'(x)$, which is our derivative. So the whole idea of a derivative is to approximate small neighborhoods around a point of a function using straight lines, where the gradient of those straight lines tell us "how much" the function is changing at that exact point, and in what direction.
Why do this? Because straight lines are easy to work with! Now instead of working with some wildly curvy (but still well-behaved) function, now you can work with a collection of straight lines and life becomes a lot simpler. Later on you will learn about linear algebra, and as you might imagine, linear algebra has a lot to do with things that are flat and straight, so having these approximations means we can do a lot of cool things very efficiently with our linear algebra tools to solve what look like otherwise unsolvable problems.
Now what do I mean by well-behaved function? Well, crucially, in the definition of the derivative, we let $h$ go to $0$. We make NO mention of whether $h$ is negative or $h$ is positive to begin with -- it's just some real number that isn't $0$. We want our function to behave in such a way that it doesn't matter if we move from below $0$ towards $0$ (i.e. $h<0$) or if we move from above $0$ towards $0$ (i.e. $h>0$). One can conceive of many functions where moving from below produces a different output than moving from above. This detail becomes very important when dealing with multidimensional functions and their derivatives, to make sure we are still dealing with well-behaved functions. Note that this requirement automatically ensures that our function is continuous (but also note that there are functions that are continuous but don't meet this requirement! Turns out that a differentiable function is continuous, but a continuous function is not necessarily differentiable! Important thing to take note of and understand).