Axial proprioceptive sensory feedback plays a crucial role in modulating locomotion, enabling vertebrates to dynamically adjust motor output in response to body movements and environmental forces. In this study, we present a spiking neuromechanical model of the zebrafish, focusing on how proprioceptive signals from Piezo2-expressing neurons modulate the activity of the spinal cord's central pattern generator (CPG) network, thus regulating the locomotor output. A spiking neural network comprising the main classes of interneurons in the zebrafish locomotor circuits, namely V2a, V0d and motoneurons, was designed based on the available electrophysiological and connectivity data. The network was coupled to a mechanical model comprising multiple joints actuated by simulated muscles. A population of axial stretch feedback neurons relayed the sensory information to the CPG network, modulating the ongoing locomotion patterns. Several novel biological experiments were conducted and compared to the results from the neuromechanical model. In line with experimental observations, proprioceptive feedback was found to accelerate the locomotor rhythm by shortening the interburst intervals of V2a neurons' activity. Additionally, when the tail was statically bent to one side, proprioceptive input altered the duty cycle of the ongoing oscillations, increasing the activity on the stretched side of the network. In cases where rhythmic tail bending was applied, the CPG network synchronized its activity to these external oscillations, which could both enhance or reduce the network’s frequency. Finally, when the kinematics of a leader fish during schooling was imposed on the tail oscillations, the resulting network activity was tightly regulated by the imposed non-periodic rhythm. Overall, this study offers new insights into how proprioceptive feedback can dynamically adjust motor output for stable and adaptive locomotion. This work also lays the groundwork for the exploration of sensorimotor integration in both individual and collective movement scenarios.