It's not a stupid question, so much as it's hard to answer. In my search for definitions, I have found some that require the matrix to be square and I have found some that do not mention that the matrix is square, but the only examples given are square. I imagine the answer is that the original definition was for square matrices but perhaps some people started using the term to describe generalizations. Or, perhaps non-square matrices of this type aren't that interesting.
The definition given in Matrix Analysis by Horn and Johnson is:
A matrix $A = [a_{ij}] \in M_{n+1}$ of the form
$$A = \begin{bmatrix} a_0 & a_1 & a_2 & \cdots & a_n \\
a_{-1} & a_0 & a_1 & \cdots & a_{n-1} \\
a_{-2} & a_{-1} & a_0 & \cdots & \vdots \\
\vdots & \vdots & \ddots & \ddots & a_1 \\
a_{-n} & a_{-n+1} & \cdots & a_{-1} & a_0 \end{bmatrix}$$
is called a Toeplitz matrix.
As far as J.M.'s comment, right after this, it defines Hankel matrices and requires that they are square as well. In fact, not long after, it says "Since ... Hankel matrices are symmetric...", which requires that Hankel matrices are square.
This set of notes I found online, which contains 98 pages about Toeplitz matrices, require them to be square by definition.
On the other hand, Matrix Analysis and Applied Linear Algebra by Meyer gives the definition:
Toeplitz matrices have constant entries on each diagonal parallel to the main diagonal.
So, this doesn't require the matrix to be square, but then they give a few examples, all of which are square.
By the way, just because MatLab or Mathematica allow something doesn't mean the definition actually allows those things, especially if it doesn't take any more work to program something.