Monte Carlo simulations are computational algorithms that use random sampling techniques to simulate a wide range of possible outcomes in complex systems. These simulations are particularly useful in fields such as finance, physics, engineering, and biology to analyze the behavior of systems and make predictions based on statistical probabilities. The simulations involve generating random numbers to represent various input parameters and then running multiple iterations to calculate the average outcome. Monte Carlo simulations are especially valuable for scenarios where analytical solutions are impractical or impossible to obtain.