This chapter introduces the foundational concepts of AI and machine learning, with emphasis on their roles in modern healthcare. It outlines traditional machine learning techniques such as decision trees and support vector machines, alongside deep learning approaches like neural networks and convolutional architectures. A comparative perspective highlights the strengths and limitations of each paradigm. The chapter also explores real-world applications across diverse healthcare domains, including diagnostics, prognosis, personalized treatment, and operational efficiency. By bridging technical foundations with clinical relevance, this chapter provides a framework for understanding how AI and machine learning are transforming health systems and patient care.