This literature review explores the critical role of load balancing in parallel machines and distributed systems, with a focus on strategies, challenges, and real-world applications. The paper comprises six main sections, covering load balancing problems, a comparative analysis of identical and unrelated parallel machines, a bibliometric analysis of existing literature, in depth paper and case study discussions, and insights into future research directions. This paper highlights the importance of load balancing in optimizing resource allocation and system stability. It emphasizes the need for adaptive and sustainable load balancing algorithms in evolving computing paradigms, making it a valuable resource for researchers, practitioners, and policymakers. It concludes by exploring future paths in this topic, namely emerging areas like edge and fog computing with swarm-like models, expanding load balancing applications and machine learning algorithms, enabling real-time load prediction and management, addressing evolving load distribution complexities.