Research on Coverage Hole Healing Techniques in Wireless Sensor Networks (WSNs) focuses on maintaining complete sensing coverage by identifying and repairing uncovered regions that arise due to node failures, energy depletion, or uneven deployment. These techniques aim to restore connectivity and sensing efficiency through mobile node repositioning, sensing range adjustment, or cooperative relocation algorithms. Recent studies employ bio-inspired optimization methods like Particle Swarm Optimization, Ant Colony Optimization, and Artificial Bee Colony to minimize movement cost and energy consumption while filling coverage gaps effectively. Machine learning-based approaches are also being explored to predict potential coverage holes and trigger proactive healing actions. Overall, coverage hole healing ensures continuous monitoring, extends network lifetime, and enhances the reliability of WSNs deployed in dynamic or large-scale environments.