Hybrid Renewable Energy Systems (HRESs) that combine photovoltaic (PV) and wind energy (WE) offer a sustainable solution for off-grid water pumping, particularly in remote or agricultural areas with limited or unreliable grid access. This review critically examines control strategies used in Hybrid Renewable Energy Water Pumping Systems (HREWPS), focusing on improvements in energy efficiency, reliability, cost-effectiveness, and adaptability to changing environmental conditions. The manuscript categorizes and compares a range of control methodologies. These include maximum power point tracking (MPPT) algorithms such as perturb and observe (P&O), incremental conductance (IC), fuzzy logic, artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and swarm intelligence techniques. Advanced motor control methods like field-oriented control (FOC), direct torque control (DTC), scalar control, and sliding mode control are also reviewed. These techniques are evaluated across motor types including induction motors (IM), brushless DC motors (BLDCM), permanent magnet synchronous motors (PMSM), switched reluctance motors (SRM), synchronous reluctance motors (SynRM), and open-end induction motors (OEIM). This study also emphasizes battery-less configurations, hybrid storage systems, and AI-enhanced energy management frameworks that optimize real-time performance and increase system resilience. Emerging technologies such as model predictive control (MPC), IoT-based remote monitoring, and blockchain-enabled microgrid energy trading are discussed as future enablers for advanced HREWPS. By integrating recent advancements and experimental findings, this review outlines a roadmap for sustainable, intelligent, and adaptive off-grid water pumping systems. It underscores the role of smart control solutions in addressing global water and energy challenges.