##E[e^{tX}]## is the Unconditional mgf of ##X##. Contrast that with the first line in the proof, which gives the Conditional mgf of ##X##.
The above shows that the Unconditional mgf is identical to the mgf of a random variable that is equally likely to take any of the values 1, 2, ..., n.
It is a theorem of probability theory that a mgf is a complete specification of a distribution, so if two random variables have the same mgf, they have the same distribution.
Hence, ##X## has the distribution of a random variable that is equally likely to take on any of the values 1, 2, ..., n. Hence, ##X## is equally likely to take on any of the values 1, 2, ..., n.