In order to solve the problem that the accuracy of indoor localization algorithm based on Received Signal Strength Indicator (RSSI) for Wireless Sensor Network (WSN) is easy to be influenced by channel interference and environment, a new indoor localization algorithm, namely FC-DNN, was proposed based on Feedback Correction of Dynamic Nearest Neighbors. Firstly, the minimum localization region was determined by partitioning the whole environment based on Voronoi diagram before positioning. Then the parameters of the path loss model for each region were calculated to obtain the precise distance between nodes. Finally, the Spearman rank correlation coefficient was introduced to select neighbor anchor nodes dynamically, and the feedback of neighbor anchor nodes was used to further improve the localization accuracy. The simulation results confirm that the proposed FC-DNN algorithm has low time complexity, small computation and low energy consumption; furthermore, compared with conventional Distance Difference Localization Algorithm (DDLA) based on RSSI and sensor network localization in COnstrained 3-D spaces (CO-3D), the average positioning error is reduced by about 15 percentage points, which can well meet the requirements of indoor localization.