Probabilistic algorithms are algorithms that use randomness to solve computational problems. These algorithms make random decisions during their execution, which allows them to efficiently approximate solutions to complex problems. One of the key advantages of probabilistic algorithms is their ability to tackle problems that are difficult or impossible to solve using deterministic algorithms. They are commonly used in areas such as machine learning, cryptography, and optimization, where precise solutions may be computationally infeasible. Probabilistic algorithms are often analyzed in terms of their expected performance and accuracy, taking into account the randomness involved in their execution. They are also used in the design of efficient algorithms for problems such as sampling, search, and optimization. Overall, probabilistic algorithms provide a powerful and versatile tool for solving challenging computational problems.