As Dick said, any scalar multiple of an eigenvector is an eigenvector- in fact, any linear combination of eigenvectors is an eigenvector.
Of course, a good way to check if any vector is any eigenvector is to use the definition of "eigenvector". If v is an eigenvector of A, corresponding to eigenvalue [itex]\lambda[/itex], then [itex]Av= \lambda v[/itex].
Here,
[tex]\begin{bmatrix}4 & 1 \\ 0 & 0\end{bmatrix}\begin{bmatrix}-1 \\ 4\end{bmatrix}= \begin{bmatrix}-4+ 4 \\ 0\end{bmatrix}= \begin{bmatrix}0 \\ 0\end{bmatrix}= 0\begin{bmatrix}-1 \\ 4\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}4 & 1 \\ 0 & 0\end{bmatrix}\begin{bmatrix} 1 \\ -4\end{bmatrix}= \begin{bmatrix}4- 4 \\ \end{bmatrix}= \begin{bmatrix}0 \\ 0 \end{bmatrix}= 0\begin{bmatrix}1 \\ -4\end{bmatrix}[/tex]
So these are both eigenvectors corresponding to eigenvalue 0.