Consider a MATLAB/OCTAVE implementation of 1D-DFT/FFT sum:
$$X[k] = \sum_{n=0}^{N-1} {x[n]e^{-j \frac {2\pi}{N} k n} } $$
where $n=0,...,N-1$ and $k=0,...,N-1$
Those identifiers are used to denote the following:
$N$: is the FFT length as in $N$-point FFT.
$x[n]$: is the discrete-time signal whose DFT $X[k]$ is to be computed.
$X[k]$: is the complex-valued DFT of the signal $x[n]$
$n$: is the discrete-time index for the signal $x[n]$ in the range $n=0,...,N-1$.
$k$: is the frequency sample index of $X[k]$, in the range $k=0,...,N-1$.
$j$: is the imaginary unit $\sqrt {-1}$ in signal processing terminology.
Note if the signal $x[n]$'s length is shorter than the FFT length, then zero padding is applied on $x[n]$ to make its length $N$. Otherwise if it's longer than $N$, then the samples after $N-1$ are ignored according to MATLAB/OCTAVE implementation.