Machine learning processes real-time data by utilizing algorithms that can instantly analyze, interpret, and make decisions based on the incoming information. As data streams in, the machine learning model continuously adjusts and refines its predictions or outputs without human intervention. The efficiency of handling real-time data can be enhanced with specialized frameworks and tools designed for speedy computations. Examples include TensorFlow and Apache Kafka. In scenarios like fraud detection, real-time recommendations, or autonomous vehicles, the ability of machine learning to swiftly process and act on real-time data is crucial for success.