Hypoxia plays a significant role in tumor progression. This study aimed to develop a hypoxia-related long noncoding RNA (lncRNA) signature for predicting survival outcomes of patients with bladder cancer (BC). The transcriptome and clinicopathologic data were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis and Lasso regression analysis were used to screened lncRNAs. Ten lncRNAs were screened out and included into the hypoxia lncRNA signature. The risk score based on hypoxia lncRNA signature could accurately predict the survival outcomes of BC patients. Immune infiltration analysis showed that six types of immune cells had significant different infiltration. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, FGFR3, and RB1 were significantly different. Gene Set Enrichment Analysis (GSEA) showed that cancer-associated pathways belonged to the high risk groups and immune-related signal pathways were enriched into the low risk group. Then, we constructed a predictive model with the risk score, age, and clinical stage, which showed a robust prognostic performance. An lncRNA-mRNA coexpression network was constructed, which contained 62 lncRNA-mRNA links among 10 lncRNAs and 40 related mRNAs. In summary, the hypoxia lncRNA signature could accurately predict prognosis, chemotherapy and immunotherapy response in patients with BC and was relevant to clinicopathologic parameters and immune cell infiltration.