Traditional local active noise control (ANC) systems aim to minimize the measured acoustic pressure in order to create a zone of quiet at the physical error sensor location. However, the effectiveness of these systems is often limited by the relatively small size of the quiet zone, which requires the physical error sensor to be placed precisely at the location where noise reduction is desired. This positioning can be inconvenient and impractical in many applications, particularly when the sensor cannot be placed directly in the desired zone of attenuation. To address these limitations, virtual sensing algorithms have been developed as an innovative solution for active noise control. Virtual sensing algorithms leverage the physical error signal, the control signal, and the system's knowledge to estimate the error signal at a remote location, referred to as the virtual location. Rather than focusing on minimizing the error at the physical sensor location, the system is designed to minimize the estimated error at the virtual location, thus generating a more effective and flexible zone of quiet at the target location, even if it is not directly accessible for sensor placement. This paper provides a comprehensive review of various virtual sensing algorithms that have been proposed for active noise control. The performance of these algorithms is evaluated through both numerical simulations and real-world experimental results. In addition to comparing the effectiveness of these algorithms, the challenges and opportunities associated with their implementation in practical ANC systems are also discussed, highlighting the potential benefits and limitations of virtual sensing in achieving broader and more dynamic noise attenuation zones