The partition of a sample space involves dividing the entire set of possible outcomes into mutually exclusive and collectively exhaustive subsets, ensuring that every possible outcome is included in one and only one subset. This concept is crucial in probability theory and statistics for simplifying complex problems and ensuring comprehensive analysis of all potential events.