My understanding of Monte Carlo is rudimentary at best, so please take my answer with a grain of salt:

In a Monte Carlo simulation, an event is simulated for some large number of trials such that a theoretical probability can be estimated. In this particular instance, I used 100K trials for an event whose theoretical (real) probability is exactly 50%.

This is similar to flipping a coin 100K times in order to estimate the probability of getting heads. It is extremely unlikely that I will get exactly 50,000 heads (exact 50%) out of my 100K coin tosses. However, the ratio of positive results (in this example: getting heads) to total trials will become more accurate as the number of trials increases.

This is known as the law of large numbers and is why Monte Carlo works in *estimating* theoretical probabilities.