Focused on the issue that existing group recommendation methods take less account of the implicit estimation of socialization relationships among group members and the use of group consensus to reduce the influence of preference conflicts, a Group Recommendation method based on implicit Trust and group Consensus (GR-TC) was proposed. The method was divided into a recommendation phase and a consensus phase. In the recommendation phase, implicit trust values were mined based on preference information and social relationships among members. The members’ individual preferences and weights, and the initial group preferences were estimated. In the consensus phase, inconsistent members were identified by consensus measurement and identification rules, a maximum harmony optimization consensus model was built, and the group recommendation list was obtained by adjusting and updating the group preferences. Experimental results show that social relationships among members affect group recommendation results, reasonable selection of implicit trust weights improves the harmony of inconsistent members. Compared with the traditional consensus feedback mechanism, the implicit trust-induced maximum harmony consensus feedback mechanism has less adjustment cost and less impact on inconsistent members.