Monte Carlo algorithms are a class of computational algorithms that rely on repeated random sampling to obtain numerical results, often used when it is difficult or impossible to compute an exact result with a deterministic algorithm. They are particularly useful for simulating complex systems and processes, such as in physics, finance, and machine learning, where they provide approximate solutions with quantifiable statistical error margins.