Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to solve mathematical problems and simulate complex systems. These methods are particularly relevant to the tech community as they are widely used in fields such as machine learning, finance, and engineering to model uncertainty, optimize processes, and make predictions, allowing researchers and developers to tackle complex problems that are difficult or impossible to solve through traditional deterministic approaches.