Automated Machine Learning (AutoML) is a process that automates the end-to-end process of applying machine learning to real-world problems, making it accessible to non-experts and improving efficiency for experts. It involves tasks such as data preprocessing, model selection, hyperparameter tuning, and model evaluation, aiming to optimize the performance of machine learning models with minimal human intervention.