Performance tuning is pivotal for managing and optimizing cluster performance in Databricks Machine Learning. It entails adjusting various configuration parameters like cluster size, hardware specifications, and Spark configurations to achieve the best performance for machine learning tasks. Proper tuning ensures efficient use of cluster resources, leading to enhanced performance and quicker execution of machine learning workloads.