So, suppose that we are Martians and know nothing about the binomial distribution; we know only that we have a parameter $q\geq 1$ and a formula describing the following probabilities
$$P(X=i)=\binom niq^{-i}\left(1-\frac1q\right)^{n-i}.\tag 1$$
($i=0,1,\cdots, n.$)
Now, assume that the outcome of our experiment is $X=0$.
Surprisingly, we are familiar with the maximum likelihood method. So, we apply it. We have to find the $q$ that maximizes
$$\left(1-\frac1q\right)^n.$$
Apparently, for any finite $q$ there is a better one. That is $q=\infty$ seems to be the maximum likelihood estimate.
Now, we suddenly learn what the binomial distribution is. We immediately conclude that $p=0$ is the solution for the "true earthly parameter." Away we sail then immediately.
EDIT
Let's try to find the maximum likelihood parameter $q\geq1$ in the case of $n$ experiments and $i$ successful outcomes assuming that the distribution is given by $(1)$. We can forget about the multiplier $\binom ni$. So, after dividing $(1)$ by $\binom ni$ take the derivative of $(1)$ with respect to $q$. And set the derivative equal to zero then solve the equation for $q$.
Here is the equation
$$(n-i)q^{-i-2}\left(1-\frac1q\right)^{n-i-1}=iq^{-i-1}\left(1-\frac1q\right)^{n-i}.$$
We will have to exclude $q=1$ from now on. However $q=1$ is certainly the solution for $n=i$. Divide both sides by $q^{-i-1}\left(1-\frac1q\right)^{n-i}$. The resulting equation is
$$(n-i)q^{-1}\left(1-\frac1q\right)^{-1}=i.$$
from here we get the expected result:
$$\hat q=\frac ni.$$
NOTE
You can see here that the MLE does have the invariance property. So it is true that if $\frac in$ is the MLE for $p$ then for $q=\frac1p$ the MLE is $\frac ni$. I did the proof above for you and I because I don't believe if theorems (invariance property this time) whose proof I've never digested.