The document discusses probabilistic algorithms and their use for solving count-distinct problems. It explains that probabilistic algorithms provide probabilistically bounded error rates rather than exact answers. The count-distinct problem aims to estimate the number of unique elements in a large dataset and is used in applications like estimating unique website visitors. The document presents the LogLog algorithm as a probabilistic solution that partitions data and tracks the maximum number of leading zeros seen to estimate the count in a memory-efficient way.