Data locality in distributed computing aims to process data on the node where it is stored, thereby minimizing the need to transfer data across the network. This strategy significantly reduces data transmission overhead, enhancing system performance and efficiency. By keeping computations close to the data source, systems like Apache Spark avoid unnecessary network traffic, leading to faster processing times.