Probabilistic computation involves algorithms that utilize random variables or stochastic processes to solve problems, often providing solutions that are faster or more efficient than deterministic approaches. This paradigm is particularly useful for dealing with uncertainty, modeling complex systems, and optimizing tasks in fields such as machine learning, cryptography, and statistical physics.