Monte Carlo methods are computational algorithms that use random sampling to solve complex mathematical or statistical problems. These methods are particularly useful for problems that involve uncertainty or probabilistic elements, where traditional analytical methods are difficult or impossible to apply. By simulating a large number of random samples, Monte Carlo methods can provide approximate solutions to problems in a wide range of fields, including physics, finance, engineering, and computer science. The name "Monte Carlo" comes from the famous casino in Monaco, where the uncle of one of the founders of the method famously rejected the idea that it was possible to predict the outcome of a roulette wheel.