Hadoop MapReduce is a programming model used for processing large data sets in a distributed computing environment. It breaks down tasks into smaller sub-tasks, which can be processed in parallel across multiple machines. This approach allows for efficient data processing and analysis, making it suitable for big data applications. The model consists of two main functions: Map and Reduce. The Map function takes input data and transforms it into key-value pairs, while the Reduce function aggregates these pairs to produce a final output. This structure enables scalable and fault-tolerant data processing across clusters of computers.