I agree with @W_D that your answer looks fine! Here's an alternate way of phrasing your answer which I find useful.
The set of all continuous functions on $M$ comes with a natural norm—a way of measuring "distance from the zero function." The norm $\|f\|_M$ of a continuous function $f$ on $M$ is defined as the supremum of $|f|$ over $M$: the smallest number greater than or equal to $|f(x)|$ for all $x \in M$ (which may be "$\infty$").
Given two continuous functions $f$ and $g$, you can think of $\|f - g\|_M$ as measuring a "distance between $f$ and $g$."
A sequence $f_n$ of continuous functions on $M$ converges uniformly to $f$ if and only if the sequence $f_n$ converges to $f$ according to the $\|\cdot\|_M$ distance. In other words, as $n$ increases, the distance $\|f_n - f\|$ eventurally drops below every positive number and stays there. (Think about why this is equivalent to the definition of uniform convergence that you already know.)
Now, define $\|f\|_N$ as the supremum of $|f|$ over $N$. Observe that $\|f\|_N \le \|f\|_M$ for all continuous functions $f$ on $M$. It follows pretty easily that if the sequence $f_n$ converges to $f$ according to the $\|\cdot\|_M$ distace, it also converges to $f$ according to the $\|\cdot\|_N$ distance.
I find this phrasing useful because it lets you break the definition of uniform convergence into two conceptually meaningful pieces: the definition of the $\|\cdot\|_M$ distance and the definition of convergence according to a distance function.
For more details, see this recent answer of mine, which just happens to be on the same topic.