Monte Carlo methods are a set of statistical techniques used to estimate numerical results through random sampling. They rely on repeated random sampling to obtain results that can approximate complex mathematical problems, making them useful in various fields such as finance, engineering, and physics. These methods are particularly effective for problems involving uncertainty or variability, such as predicting the outcome of stock market investments or assessing risks in project management. By simulating a large number of scenarios, Monte Carlo methods help in understanding the range of possible outcomes and their probabilities.