The field of drug discovery has seen significant advancements in recent years with AI and machine learning techniques. The integration of quantum computing in the pipelines provides new opportunities. Recently, huge progress was achieved in quantum hardware, the main players announce the achievement of fault-tolerant devices by 2030 in their roadmaps. This book chapter provides an introduction into Quantum Machine Learning (QML) algorithms and an overview of how these algorithms can be used to accelerate various stages of the drug discovery pipeline. Key QML algorithms are described, along with examples of successful case studies in drug discovery. The chapter also examines the challenges and limitations of current QML approaches, as well as future directions for the field.