This chapter introduces the Bees Algorithm, a nature-inspired optimisation method that mimics the foraging behaviour of honey bees. It explains that nature-inspired optimisation, including Swarm Intelligence (SI) and Evolutionary Algorithms (EA), takes inspiration from biological systems to solve complex problems. The chapter describes the honey bee foraging process, where scout bees explore the environment for food sources and recruit foragers through a waggle dance to exploit promising areas. The Bees Algorithm mirrors this process, using artificial bees as agents to search the solution space. Scout bees perform global exploration while foragers conduct local exploitation around promising solutions. The algorithm includes mechanisms like the waggle dance to allocate search effort, and neighbourhood shrinking and site abandonment to adapt the search strategy. The chapter also discusses the representation scheme, initialisation process, and stopping criterion of the Bees Algorithm. It then compares the Bees Algorithm with other metaheuristics, highlighting its similarities and differences with other bee-inspired and population-based methods, and two standard optimisation procedures: Variable Neighbourhood Search (VNS) and Luus and Jaakola (LJ) Search. The chapter concludes by reviewing the main application areas of the Bees Algorithm.