Cuckoo Search (CS) is a nature-inspired metaheuristic algorithm developed by Xin-She Yang and Suash Deb in 2009. This paper reviews the fundamental ideas of CS, its recent developments, and applications. CS is efficient in solving global optimization problems due to its unique search mechanisms, which include both local and global search capabilities. The algorithm uses Lévy flights for global exploration and a switching probability to control the balance between local and global searches. CS has been applied in various fields, including engineering design, machine learning, and computational intelligence, demonstrating superior performance over other algorithms in many cases. The paper also discusses the essence of optimization algorithms, their efficiency, and the challenges in theoretical analysis and parameter tuning. Future research directions include addressing the gap between theory and practice, improving parameter tuning, and expanding the application of CS to problems with a larger number of variables.Cuckoo Search (CS) is a nature-inspired metaheuristic algorithm developed by Xin-She Yang and Suash Deb in 2009. This paper reviews the fundamental ideas of CS, its recent developments, and applications. CS is efficient in solving global optimization problems due to its unique search mechanisms, which include both local and global search capabilities. The algorithm uses Lévy flights for global exploration and a switching probability to control the balance between local and global searches. CS has been applied in various fields, including engineering design, machine learning, and computational intelligence, demonstrating superior performance over other algorithms in many cases. The paper also discusses the essence of optimization algorithms, their efficiency, and the challenges in theoretical analysis and parameter tuning. Future research directions include addressing the gap between theory and practice, improving parameter tuning, and expanding the application of CS to problems with a larger number of variables.