Guidance, Navigation, and Control (GNC) underpin autonomous systems across aerial, terrestrial, surface, and underwater domains. Over the last five years, progress has accelerated with stronger onboard compute, maturing sensors, and the rise of learning-assisted methods. This paper offers a structured review of recent GNC advances (2020–2025), organized around three pillars: (i) guidance and trajectory planning, covering real-time optimal control and modern motion planners; (ii) navigation and state estimation, including multi-sensor fusion, INS/GNSS integration, visual/lidar-inertial odometry, and information-aiding for GNSS-denied operation; and (iii) control strategies, spanning linear/nonlinear, robust and model-predictive control, adaptive and learning-based designs. Beyond summarizing contributions, we identify converging trends—most notably the integration of physics-based models with data-driven components—and map open challenges in scalability, verification, energy efficiency, benchmark comparability, and robustness under distribution shift. We propose a concise taxonomy to harmonize terminology, relate methods across domains and levels of autonomy, and enable fair comparison. By consolidating key results and highlighting research opportunities, this review aims to guide researchers in selecting and combining GNC methods that meet real-time, safety, and deployment constraints across the full GNC stack and all four operating domains.