The languages currently popular for bioinformatics work are Python, Java, R, Perl, and BASH, though the use of Perl is gradually declining. Note that Python has become the most popular language in a general context, so it's natural that it's the most popular in bioinformatics too. Of course 'most popular' doesn't mean 'best'. Pick a computer language and I'll point you to some publication that uses that language in a bioinformatics context (perhaps excepting COBOL, and RPG).
Some bioinformaticists spend most of their time performing analyses using existing software, perhaps using a scripting language like Python or BASH to 'glue' together existing programs or to control the submission of jobs to a computational cluster. Scripts and packages using the R language are often used in these analysis pipelines to perform sophisticated statistical analysis and visualizations.
Other bioinformaticists are developing new algorthims. In these cases computational speed can be very important, so languages like C, C++, or Java are often used. However, newer languages like Go, Julia, and Rust are also used, according to the taste of the researcher. New machine learning tools are often prototyped using MATLAB.
If your interest is primarily biology (biochemistry, virology, and immunology) then you'll want to focus on learning the biology, and supplement it with Python, BASH, and R. If your interest is primarily in developing new algorithms, then focus on statistics, and computer science. You'll still want to learn Python, BASH, and R, but you'll also want to add something like C++ or Java. The good news is that once you've learned 2 or 3 computer languages, you can pick up additional languages much more easily.