A Resilient Distributed Dataset (RDD) is a fundamental data structure of Apache Spark, designed to handle large-scale data processing across a distributed computing environment while providing fault tolerance and parallel processing. It allows users to perform in-memory computations on large clusters in a fault-tolerant manner, enabling efficient data sharing and manipulation across nodes.