Mechanical noise reduction has evolved into a multidisciplinary field driven by increasing performance demands, regulatory pressures, and the complexity of modern mechanical systems. This review consolidates advances spanning passive, active, semi-active, hybrid, and AI-enhanced methodologies to provide a comprehensive assessment of current capabilities and emerging opportunities. Basic noise-generation processes- including gear meshing, fluid structure interaction, and aerodynamic excitation are discussed together with the route taken by the noise in mechanical assemblies. Recent progress in materials engineering, including metamaterials, nanostructured composites, and additive-manufactured acoustic structures, has enabled lightweight yet high-performance solutions that overcome the bandwidth and mass limitations of traditional passive treatments. Meanwhile, developments in active noise control, distributed sensing, and adaptive algorithms have expanded controllability across low-frequency and dynamic environments. Integrating smart materials with AI-driven prediction, digital twinning, and multi-objective optimization is reshaping the design of intelligent acoustic systems capable of continuous learning and adaptation. Application-focused innovations in automotive, aerospace, manufacturing, and HVAC systems illustrate how tailored noise-control strategies enhance safety, comfort, and operational efficiency. The review identifies critical research gaps related to the co-design of materials and control architectures, multifunctional acoustic structures, and cross-disciplinary approaches inspired by biological and micro-structured surfaces. Together, these directions signal a transition toward next-generation noise-control solutions that function as adaptive, sustainable, and cyber-physical components within future mechanical systems